The gather-scatter models used by graph computing systems [1]} or even the coarse-grained filter-expand models used by graph mining-systems [2]} are not effective for subgraph matching. Therefore, subgraph matching has been subject of active research for the last 2 decades. These works normally only support static graphs and focus on developing number of techniques to optimize the matching order [3]}, [4]}, prune the false candidates [5]}, [4]}, optimize index structure [7]}, [8]}, reduce the data redundancy [9]}, search for the multiple queries together [10]}, and parallelization [11]}, [12]}.
The way these systems could work for real-time subgraph matching is getting a graph snapshot at a point in time, and running subgraph matching on that snapshot. However, when the interval between two snapshots gets smaller, the redundancy plagues their performance.
